DEDIC: Density Estimation Clustering Method Using Directly Interconnected Cores

Lin, Yisen; Zhang, Xinlun; Liu, Lei; Qu, Huichen

doi:10.1109/access.2022.3229582

Cited by 3 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The time complexity analysis of the remaining part of algorithm 1 is as follows: Line8, according to descending to the time complexity is to sort the list of . Line11, the complexity of MakeClusterBackbones(Algorithm2) is ,where is an upper limit of the number of generated clusters 31 . Consider the worst case, and .…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Finally, the overall complexity is . Line12, the complexity of MergeNonBackbonesPoints (Algorithm3) is 31 . Based on the same analysis, the complexity is .…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Line11, the complexity of MakeClusterBackbones(Algorithm2) is ,where is an upper limit of the number of generated clusters 31 . Consider the worst case, and .…”

Section: Proposed Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Research on stress curve clustering algorithm of Fiber Bragg grating sensor

Lin

Wang

et al. 2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

The global stress distribution and state parameter analysis of the building's main structure is an urgent problem to be solved in the online state assessment technology of building structure health. In this paper, a stress curve clustering algorithm of fiber Bragg grating stress sensor based on density clustering algorithm is proposed. To solve the problem of large dimension and sparse sample space of sensor stress curve, the distance between samples is measured based on improved cosine similarity. Aiming at the problem of low efficiency and poor effect of traditional clustering algorithm, density clustering algorithm based on mutual nearest neighbor is used to cluster. Finally, the classification of the daily stress load characteristics of the sensor is realized, which provides a basis for constructing the mathematical analysis model of building health. The experimental results show that the stress curve clustering method proposed in this paper is better than the latest clustering algorithms such as HDBSCAN, CBKM, K-mean++,FINCH and NPIR, and is suitable for the feature classification of stress curves of fiber Bragg grating sensors.

show abstract

Section: Proposed Methodsmentioning

confidence: 99%

“…Finally, the overall complexity is . Line12, the complexity of MergeNonBackbonesPoints (Algorithm3) is 31 . Based on the same analysis, the complexity is .…”

Section: Proposed Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Research on stress curve clustering algorithm of Fiber Bragg grating sensor

Lin

Wang

et al. 2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the above article [1], one reference [2] was missing. This reference should be inserted between the original references [9] and [10], that is, the order of the reference [10] and subsequent references increases by one.…”

mentioning

confidence: 99%

“…This is a fundamental technique in various fields such as pattern recognition and machine learning. As an efficient data analysis tool, clustering is widely adopted in fields such as medical images [1], bioinformatics [2], and fraud detection [3].…”

mentioning

confidence: 99%